16S rRNA gene amplicon sequencing of the microbial community after treated with antibiotic

This study used 16S rRNA gene sequencing data with machine learning to predict the relationship between the characteristics of antibiotics and the composition and function of bacterial communities in aquatic habitats. The aquatic microcosms were treated with 50 commonly used antibiotics referred to 9 classes. The present study aimed to (1) study the composition of the aquatic microbial community after nine different types of antibiotics treatment; (2) establish a predictive model of antibiotic properties on the composition and function of aquatic microbial communities. Our study accurately predicted the contribution of antibiotic characteristics to the aquatic ecosystem and provided a guidance of the further development of eco-friendly